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Here M ( y l 1, …, y l p ) is defined in (1.1) and ρ ( y l 1, …, y l p ) is the least eigenvalue of M ( y l 1, …, y l p ).
for y l ∈ Θ.
Clearly, E Y l, k = 0.
$$\end{documentt} y L ≤ y ≤ y U.
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H-Y L collected the data.
where y ∈ L 2 ( I ).
Note that g ′ ( y ) ∈ L 2.
for every y ∈ L { F n }.
I(1 L,y)≤ L y for each y∈L.
C L and Y L, MD are assistant professors.
Emissions (i): In this case, E i (y, L, M) = E i (y, L, l).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com